Addressing the gaps in enterprise GPT solutions

There are thousands of Generative AI (GenAI) tools and copilots available today. With the speed of new tools and copilots launching daily, many organizations are turning to “for enterprise" offers to address their AI needs when it comes to security and protection. While these platforms do offer advantages, it's crucial to understand that simply adopting an enterprise GPT isn’t enough. 

Let's dive into the complexities that persist even with an enterprise GPT solution.

Transforming the way you work

First, we must applaud any organization looking to transform the way their workforce works with GenAI. This includes supercharging productivity, amplifying creativity, and optimizing processes. With enterprise options by solutions like ChatGPT, Microsoft 365 Copilot, and Enterprise Pro with Perplexity, organizations are gaining the ability to:

1. Identify impact with visibility into actions taken and hours assisted
2. Remain in control with the trust that data is isolated and never used to train foundation models
3. Detect non-compliant use

While there is an appeal to these enterprise grade solutions, there’s still several critical challenges that organizations will face if they stop here: 

1. Inability to drive traffic to preferred AI services

One of the primary challenges organizations face is ensuring that employees use approved AI services rather than resorting to potentially unsecured alternatives. Even with an enterprise GPT in place, there's no guarantee that users will automatically gravitate towards the sanctioned platform. Organizations need a robust strategy to route AI traffic to their preferred destination, whether it's a CoPilot portal or an enterprise ChatGPT login.

This approach not only promotes the use of approved services but also mitigates the risk of "Shadow AI" – the unauthorized use of AI tools that can potentially compromise data security and compliance.

2. Risk mitigation across multiple AI services

While an enterprise GPT provides a secure environment for AI interactions, it's not uncommon for organizations to use multiple AI services to meet diverse needs. This multi-service landscape introduces new risks that need to be managed effectively. And while organizations might block access to well-known AI platforms, new tools emerge daily (for example:  Deepseek), creating an ever-evolving challenge for security and compliance teams.

Organizations must implement comprehensive access controls that extend beyond their primary enterprise GPT to encompass all approved (and potentially unapproved) GenAI services. This includes the ability to inspect both requests and responses, providing business-level insights, maintaining an audit trail for legal and compliance purposes, and implementing sensitive data detection to prevent data leakage to external parties.

3. Advanced use-cases and cost optimization

Enterprise GPTs often come with limitations in terms of customization and integration with existing enterprise data and systems. For organizations looking to implement advanced AI use-cases or optimize costs, additional solutions are necessary.

This might involve creating a private model portal that connects to preferred AI model destinations via API or secure IAM access. Such a setup allows for the implementation of guardrails, access controls, and audit trails while also enabling integration with enterprise data context sources and vector databases for managed RAG (Retrieval-Augmented Generation).

Another challenge lies in striking the right balance between allowing direct access to approved AI services and providing managed solutions for more complex use-cases. Organizations need the flexibility to offer both options, enabling users to access services like Perplexity directly while also providing a private portal with policy-defined assistants and context data sources for more specialized tasks.

4. Complete compliance and governance

Enterprise GPTs provide a level of security and compliance, but they may not cover all the specific regulatory requirements of your industry or region. Organizations need to implement additional layers of governance to ensure that all AI interactions, regardless of the platform, adhere to internal policies and external regulations. For instance, a healthcare organization implementing AI for patient data analysis must establish additional safeguards beyond what Enterprise GPTs offer to ensure HIPAA compliance, such as audit trails that track every interaction with protected health information, specialized consent management processes, and customized access controls that align with their particular patient privacy framework and state-specific healthcare regulations.

5. Integration with existing infrastructure

While enterprise GPTs offer powerful capabilities, they often exist as standalone solutions. Organizations face the challenge of seamlessly integrating these tools with their existing IT infrastructure, including SIEM systems for security monitoring, knowledge management systems, and other business-critical applications.

Best steps forward

The AI landscape is always evolving, and what works today may not be sufficient tomorrow. Organizations need a GenAI security approach that keeps pace with rapid technological advancements. A comprehensive security solution must go beyond individual enterprise GPTs to provide:

- Coverage across thousands of GenAI apps, ensuring visibility and governance.

- Network detections for traffic analysis and pattern recognition.

- Robust compliance controls to mitigate risk and prevent data leakage.

With SurePath AI, organizations can confidently stay ahead with securing their GenAI ecosystem, maintaining compliance, and ensuring visibility across all GenAI interactions.

If you're ready to take compelte control of your GenAI security, book a demo with our human team or start a trial today.